CAR is a new technology that has not yet been implemented in IC form, therefore is no known prior art for processing methods and hardware for CAR signals.
The most straightforward method for CAR signal processing is to utilize a matched filter technique, which is common in radar signal processing. This technique consists of correlating the received signal against a library of reference signals, each of which corresponding to a scattering object at a particular range, velocity, and bearing angles. When the received signal contains a component due to a scattering object at the reference location, a strong output is produced, with the strength indicating the scattering cross section at the reference location. This technique is effective, but requires an often prohibitive amount of memory to store the reference signals, and significant computation to perform the correlations in a CPU (for example).
Comparing this invention to traditional digital beamforming radar, this invention reduces the computation time and/or the digital hardware complexity significantly, with an even bigger advantage for large arrays. Digital beamforming arrays possess a separate receiver and analog to digital converter (ADC) behind each of the array elements. The large number of output signals are then digitized and the directional beams with desired characteristics are produced by forming linear combinations of the element signals. This technique requires that digital information from all of the elements across the array be weighted and combined, with a separate linear combination for each beam position. This is highly computationally intensive and introduces significant latency for large arrays due to the limited speed with which basic digital calculations (e.g., multiplications) may be made.
One may try to reduce computation time by implementing the weighting and combining in digital hardware, thereby performing the computations in parallel. However, the fact that digital beamforming combines signals from all the elements creates highly complex combining networks that quickly become unfeasible as the array gets large and even more particularly so if the array is a two dimensional (2D) array.
Because the range, velocity, and spatial information for CAR are interdependent, it is not apparent that one may apply a simple set of multiplications and then utilize FFTs to produce estimates of range, velocity, and bearing angles.